Learning Bayesian Networks

Neapolitan, Richard E.

ISBN 10: 0130125342 / ISBN 13: 9780130125347

Editore: Pearson, 2019

Riguardo questo articolo

Used book in good and clean conditions. Pages and cover are intact. Limited notes marks and highlighting may be present. May show signs of normal shelf wear and bends on edges. Item may be missing CDs or access codes. May include library marks. Fast Shipping. Codice articolo ZWM.DVEJ

Dati bibliografici

Titolo: Learning Bayesian Networks

Casa editrice: Pearson

Data di pubblicazione: 2019

Legatura: Rilegato

Condizione: good

Descrizione articolo

Riassunto:

In this first edition book, methods are discussed for doing inference in Bayesian networks and inference diagrams. Hundreds of examples and problems allow readers to grasp the information. Some of the topics discussed include Pearl's message passing algorithm, Parameter Learning: 2 Alternatives, Parameter Learning r Alternatives, Bayesian Structure Learning, and Constraint-Based Learning. For expert systems developers and decision theorists.

L'autore:

Richard E. Neapolitan has been a researcher in Bayesian networks and the area of uncertainty in artificial intelligence since the mid-1980s. In 1990, he wrote the seminal text, Probabilistic Reasoning in Expert Systems, which helped to unify the field of Bayesian networks. Dr. Neapolitan has published numerous articles spanning the fields of computer science, mathematics, philosophy of science, and psychology. Dr. Neapolitan is currently professor and chair of Computer Science at Northeastern Illinois University.